The Dynamics of Cryptococcus neoformans Cell and Transcriptional Remodeling during Infection
Bibliographic record
Abstract
The phenotypic plasticity of Cryptococcus neoformans is widely studied and demonstrated in vitro, but its influence on pathogenicity remains unclear. In this study, we investigated the dynamics of cryptococcal cell and transcriptional remodeling during pulmonary infection in a murine model. We showed that in Cryptococcus neoformans, cell size reduction (cell body ≤ 3 µm) is important for initial adaptation during infection. This change was associated with reproductive fitness and tissue invasion. Subsequently, the fungus develops mechanisms aimed at resistance to the host’s immune response, which is determinant for virulence. We investigated the transcriptional changes involved in this cellular remodeling and found an upregulation of transcripts related to ribosome biogenesis at the beginning (6 h) of infection and a later (10 days) upregulation of transcripts involved in the inositol pathway, energy production, and the proteasome. Consistent with a role for the proteasome, we found that its inhibition delayed cell remodeling during infection with the H99 strain. Altogether, these results further our understanding of the infection biology of C. neoformans and provide perspectives to support therapeutic and diagnostic targets for cryptococcosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".